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finesub-diarizen-cpu
spurtcarl/finesub-diarizen-cpu
finesub-diarizen-cpu is a machine learning model from spurtcarl. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-nc-4.0.
Non-commercial use only (CC BY-NC 4.0). This is a format conversion made for FineSub's speaker diarization, so it can run without the diarizen and pyannote.audio packages. It is not a new model and was not retrained.
Access
Public
Updated Sep 21, 2026
Repo size
306 MB
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At a glance
- License
- cc-by-nc-4.0
- Access
- Public
- Created
- Sep 21, 2026
- Updated
- Sep 21, 2026
- SHA
- 5b6014b6
Base models
Model card
From the Hugging Face model README
DiariZen (wavlm-large-s80-md-v2) as TorchScript — CPU build
Non-commercial use only (CC BY-NC 4.0). This is a format conversion made for
FineSub's speaker diarization, so it can run without the
diarizen and pyannote.audio packages. It is not a new model and was not retrained.
| File | What it is | From | Licence |
|---|---|---|---|
diarizen_segmentation.ts | WavLM-Large (pruned) + Conformer local segmentation, traced forward pass | BUT-FIT/diarizen-wavlm-large-s80-md-v2 @ 027b3e22 | CC BY-NC 4.0 |
diarizen_embedding.ts | WeSpeaker ResNet34 speaker-embedding network (the part after fbank), traced | pyannote/wespeaker-voxceleb-resnet34-LM @ 837717dd | CC BY 4.0 |
plda/plda.npz, plda/xvec_transform.npz | PLDA and x-vector transform, copied unchanged | BUT-FIT/diarizen-wavlm-large-s80-md-v2 | CC BY-NC 4.0 |
The bundle carries the most restrictive of the three: CC BY-NC 4.0.
CPU only
TorchScript records the device it was traced on. These files were traced on CPU and run only on CPU; the CUDA build is spurtcarl/finesub-diarizen-cuda.
What changed from the originals
- Traced with
torch.jit.trace(torch 2.11.0+cu128); not frozen, not quantised, weights unchanged. - The traced modules were checked against the eager originals bit for bit, repeated calls at batch sizes 1–3, before writing.
- Everything else DiariZen does — windowing, powerset decoding, VBx clustering — is reimplemented in FineSub; see its documentation for how that port was characterised.
Export script: tools/diarizen_export/export_diarizen.py in the FineSub repository.
Credit
DiariZen is by BUT Speech@FIT. Please cite their work (see the original model card) and the WeSpeaker paper (Wang et al., ICASSP 2023) for the embedding model. Some of DiariZen's training data is research-only, which is why its weights — and therefore this conversion — may not be used commercially.
- License
- cc-by-nc-4.0
- Created
- Sep 21, 2026
- Updated
- Sep 21, 2026